Exploring the Ecology of Human Stories
In this talk, I will talk about our efforts at the Computational Story Lab to quantify human stories of all kinds. I'll present some examples of our "lexical meters"---online, interactive instruments that use social media and other texts to quantify population rates of a wide array of human behavior such as wealth, exercise levels, obesity rates, and sleep insufficiency. I will present evidence for how 10 diverse natural languages appear to contain a striking frequency-independent positive bias, describing how this phenomenon plays a key role in our hedonometer's performance, and how it may more deeply reflects human nature. I will present hedonometric analysis of works of literature and movies, and then discuss our work on building the Panometer, introducing our latest instrument: the Lexicocalorimeter, a principled meter that turns phrases into calories. Along the way, I will point to a number other diverse projects being carried by our team, ranging from the stories of sports to the failures of large corpora such as Google Books. I will close with some thoughts on the nature of human stories and venture that a science of stories now has the potential to now be developed in full, and that its success will be crucial in
understanding the evolution, stability, and fracturing of social systems.
Peter Sheridan Dodds is a Professor at the University of Vermont (UVM) working on system-level problems in many fields, ranging from sociology to physics. He is Director of the UVM's Complex Systems Center, co-Director of UVM's Computational Story Lab, and a visiting faculty fellow at the Vermont Advanced Computing Core. He maintains general research and teaching interests in complex systems and networks with a current focus on sociotechnical and psychological phenomena including collective emotional states, contagion, language, and stories. His methods encompass large-scale sociotechnical experiments, large-scale data collection and analysis, and the formulation, analysis, and simulation of theoretical models. Dodds's training is in theoretical physics, mathematics, and electrical engineering with extensive formal postdoctoral and research experience in the social sciences. Dodds has received funding from NSF, NASA, ONR, and the MITRE Corporation, among others, notably being awarded an NSF CAREER by the Social and Economic Sciences Directorate.